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Prediction analysis model of integrated carrying capacity using set pair analysis

机译:集对分析的综合承载力预测分析模型

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As a comprehensive capacity of nature, society and humans, integrated carrying capacity (ICC) is the driving force of regional socioeconomic development. Only when an ecosystem is under-loaded can socioeconomic development be sustainable. ICC is an accumulative total value of each indicator's carrying capacity, which reflects a static status. The ICC prediction analysis is one prerequisite to making economic development plans. In this paper, a dynamic prediction model is developed by using the model of set pair analysis (SPA) to predict the growth tendency of ICC. The model is tested in a case comprising eight coastal cities in Yangtze. (1) The average error rate of this prediction model is merely 0.38%, and the lowest error rate is 0.01%. The SPA model is better to predict ICC tendencies. (2) According to the national development plan, the eight cities' ICC is predicted in 2015. (3) The prediction model is a multiple method that can contain all indicators of ICC. This model can estimate the maximal carrying capacity of a natural ecosystem to make the most suitable economic development policy. The socioeconomic development must comply with the under-loaded capacity to maintain sustainable development. (C) 2015 Elsevier Ltd. All rights reserved.
机译:作为自然,社会和人类的综合能力,综合承载力(ICC)是区域社会经济发展的动力。只有当生态系统负荷不足时,社会经济发展才能可持续。 ICC是每个指标的承载能力的累积总价值,反映了静态状态。 ICC预测分析是制定经济发展计划的前提之一。本文利用集对分析(SPA)模型建立了动态​​预测模型,以预测ICC的发展趋势。该模型在包含长江沿岸八个沿海城市的案例中进行了测试。 (1)该预测模型的平均错误率仅为0.38%,最低错误率为0.01%。 SPA模型可以更好地预测ICC趋势。 (2)根据国家发展规划,对2015年八个城市的ICC进行预测。(3)预测模型是可以包含ICC所有指标的多元方法。该模型可以估计自然生态系统制定最合适的经济发展政策的最大承载能力。社会经济发展必须遵守负荷不足的能力,以维持可持续发展。 (C)2015 Elsevier Ltd.保留所有权利。

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